Many valuable reversible watermarking algorithms have been published up to today, mostly in the field of image processing, there are also some methods for reversible audio data hiding have been proposed, which can be categorized into three classes based on the embedding data domain: waveform domain, spectral domain and compressed data domain.
With the waveform as the embedding data domain, data embedding is carried out directly on the audio waveform, this type of data hiding techniques is usually simple and less computation is required. This technique makes use of an integer coefficient predictor to obtain the prediction error of the original audio. Location map that records expandability of audio samples are then embedded together with the watermark by prediction error expansion.
For data hiding using spectral domain, the audio waveform is first transformed to frequency domain by integer conversion before the embedding process, and inverse transform is needed after embedding to give out the stego audio waveform. For example, Integer Discrete Cosine Transform (intDCT) in the transformation of the audio waveform uses hash function to extract feature value of the original content, and amplitude expansion is employed in high frequency spectrum to embed the feature value for tamper detection. As the method is intended for tamper detection, most of the space is occupied by the overhead including the feature value and positional data, so not much embedding space is left for other payload.
Reversible audio watermarking techniques with compressed embedding data domain compress the unimportant parameters in the audio to provide space for data embedding, and the compression algorithm used usually utilizes linear prediction model. For example, a reversible watermarking method for compressed speech by entropy coding is provided and this scheme can be applied in different speech coding standards. However, it has a limited embedding capacity.